Few areas of monetary economics have been studied as extensively as the transmission mechanism. The literature on this topic has evolved substantially over the years, following the waxing and waning of conceptual frameworks and the changing characteristics of the financial system. In this paper, taking as a starting point a brief overview of the extant work on the interaction between capital regulation, the business cycle and the transmission mechanism, we offer some broader reflections on the characteristics of the transmission mechanism in light of the evolution of the financial system. We argue that insufficient attention has so far been paid to the link between monetary policy and the perception and pricing of risk by economic agents - what might be termed the "risk-taking channel" of monetary policy. We develop the concept, compare it with current views of the transmission mechanism, explore its mutually reinforcing link with "liquidity" and analyse its interaction with monetary policy reaction functions. We argue that changes in the financial system and prudential regulation may have increased the importance of the risk-taking channel and that prevailing macroeconomic paradigms and associated models are not well suited to capturing it, thereby also reducing their effectiveness as guides to monetary policy.

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Capital Regulation, Risk-Taking and Monetary Policy: A Missing Link in the Transmission Mechanism?

We analyze the impact of monetary policy on the supply of bank credit. Monetary policy affects both loan supply and demand, thus making identification a steep challenge. We therefore analyze a novel, supervisory dataset with loan applications from Spain. Accounting for time-varying firm heterogeneity in loan demand, we find that tighter monetary and worse economic conditions substantially reduce loan granting, especially from banks with lower capital or liquidity ratios; responding to applications for the same loan, weak banks are less likely to grant the loan. Finally, firms cannot offset the resultant credit restriction by applying to other banks. (JEL E32, E44, E52, G21, G32)

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Credit Supply and Monetary Policy: Identifying the Bank Balance-Sheet Channel with Loan Applications

This paper investigates risk and stability features of Islamic banking using a sample of 553 banks from 24 countries between 1999 and 2009. Small Islamic banks that are leveraged or based in countries with predominantly Muslim populations have lower credit risk than conventional banks. In terms of insolvency risk, small Islamic banks also appear more stable. Moreover, we find little evidence that Islamic banks charge rents to their customers for offering Sharia compliant financial products. Our results also show that loan quality of Islamic banks is less responsive to domestic interest rates compared to conventional banks.

https://hal-unilim.archives-ouvertes.fr/hal-00915115/document

Risk in Islamic Banking

Considering the fundamental role played by small and medium sized enterprises (SMEs) in the economy of many countries and the considerable attention placed on SMEs in the new Basel Capital Accord, we develop a distress prediction model specifically for the SME sector and to analyze its effectiveness compared to a generic corporate model. The behavior of financial measures for SMEs is analyzed and the most significant variables in predicting the entities' credit worthiness are selected in order to construct a default prediction model. Using a logit regression technique on a panel of over 2,000 US firms (with sales less than $65 million) over the period 1994-2002, we develop a one-year default prediction model. This model has an out of sample prediction power which is almost 30% higher than a generic corporate model. An associated objective is to observe our model's ability to lower bank capital requirements considering the new Basel Capital Accord's rules for SMEs.

https://papers.ssrn.com/sol3/Delivery.cfm/abac_234.pdf?abstractid=1007548&mirid=1

Modeling Credit Risk for SMEs: Evidence from the US Market

Forecasting Bankruptcy More Accurately: A Simple Hazard Model

Despite a surge in the research efforts put into modeling credit and default risk during the past decade, few studies have incorporated the impact that macroeconomic conditions have on business defaults. In this paper, we estimate a duration model to explain the survival time to default for borrowers in the business loan portfolio of a major Swedish bank over the period 1994–2000. The model takes both firm-specific characteristics, such as accounting ratios and payment behaviour, loan-related information, and the prevailing macroeconomic conditions into account. The output gap, the yield curve and consumers’ expectations of future economic development have significant explanatory power for the default risk of firms. We also compare our model with a frequently used model of firm default risk that conditions only on firm-specific information. The comparison shows that while the latter model can make a reasonably accurate ranking of firms’ according to default risk, our model, by taking macro conditions into account, is also able to account for the absolute level of risk.

Corporate credit risk modeling and the macroeconomy

This paper builds on the credit-scoring literature and proposes a method to calculate portfolio credit risk. Individual default risk estimates are used to compose a value-at-risk (VaR) measure of credit risk. In general, credit-scoring models suffer from a sample-selection bias. The starting point is therefore to estimate an unbiased scoring model using the bivariate probit approach. The paper uses a large data set with Swedish consumer credit data that contains extensive financial and personal information on both rejected and approved applicants. We study how marginal changes in a default-risk-based acceptance rule would shift the size of the banks loan portfolio, its VaR exposure and average credit losses. Finally, we compare the risk in the sample portfolio with that in an efficiently provided portfolio of equal size. The results show that the size of a small consumer loan does not affect associated default risk, implying that the bank provides loans in a way that is not consistent with default-risk minimization. VaR calculations indicate that an efficient selection (by means of a default-riskbased rule) of loan applicants can reduce credit risk by up to 80%. 2002 Elsevier Science B.V. All rights reserved.

/pdf/bank-lending-policy-credit-scoring-and-value-at-risk-54ffzzmmj2.pdf

Bank lending policy, credit scoring and value-at-risk

We show that collateral plays an important role in the design of debt contracts, the provision of credit, and the incentives of lenders to monitor borrowers. Using a unique data set from a large bank containing timely assessments of collateral values, we find that the bank responded to a legal reform that exogenously reduced collateral values by increasing interest rates, tightening credit limits, and reducing the intensity of its monitoring of borrowers and collateral, spurring borrower delinquency on outstanding claims. We thus explain why banks are senior lenders and quantify the value of claimant priority.

/pdf/collateralization-bank-loan-rates-and-monitoring-4o5bgrzwam.pdf

Collateralization, bank loan rates and monitoring

This paper aims at improving our understanding of internal risk rating systems (IRS) at large banks, of the way in which they are implemented, and at verifying if IRS produce consistent estimates of banks’ loan portfolio credit risk. An important property of our work is that the size of our data set allows us to derive measures of credit risk without making any assumptions about correlations between loans, by applying Carey’s [Carey, Mark, 1998. Credit risk in private debt portfolios. Journal of Finance LIII (4), 1363–1387] non-parametric Monte Carlo re-sampling method. We find substantial differences between the implied loss distributions of two banks with equal “regulatory” risk profiles; both expected losses and the credit loss rates at a wide range of loss distribution percentiles vary considerably. Such variation will translate into different levels of required economic capital. Our results also confirm the quantitative importance of size for portfolio credit risk: for common parameter values, we find that tail risk can be reduced by up to 40% by doubling portfolio size. Our analysis makes clear that not only the formal design of a rating system, but also the way in which it is implemented (e.g. a rating grade composition; the degree of homogeneity within rating classes) can be quantitatively important for the shape of credit loss distributions and thus for banks’ required capital structure. The evidence of differences between lenders also hints at the presence of differentiated market equilibria, that are more complex than might otherwise be supposed: different lending or risk management “styles” may emerge and banks strike their own balance between risk-taking and (the cost of) monitoring (that risk).

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Internal ratings systems, implied credit risk and the consistency of banks’ risk classification policies

This paper re-examines the empirical relationship between financial and economic development while (i) taking into account their dynamics and (ii) differentiating between stock market and banking sector development. We study the cointegration and causality between the real and the financial sector for 26 countries. Our time series analysis suggests that the evidence in support of a finance-led growth is weak once we take into account the dynamics of financial development and growth. We show that causality patterns depend on whether countries' financial development stems from the stock market or the banking sector. Stock market development tends to cause growth, while a reverse or bi-directional causality is present between banking sector development and output growth. We also bring evidence that causality patterns differ between market-based and bank-based economies suggesting that financial structure influences the causal direction between financial and economic development. Thus, the relation between financial and economic development is likely to be more complex than suggested in earlier studies.

/pdf/finance-and-growth-time-series-evidence-on-causality-3zcjq04it8.pdf

Kasper Roszbach

Papers

Corporate credit risk modeling and the macroeconomy

Bank lending policy, credit scoring and value-at-risk

Collateralization, bank loan rates and monitoring

Internal ratings systems, implied credit risk and the consistency of banks’ risk classification policies

Finance and Growth: Time Series Evidence on Causality